In the Hongze Area, the reservoirs vary rapidly laterally and are controlled by many factors, such as structure, lithology, oil source, and so on. S-wave well log curves are calculated from an equation derived from mu...In the Hongze Area, the reservoirs vary rapidly laterally and are controlled by many factors, such as structure, lithology, oil source, and so on. S-wave well log curves are calculated from an equation derived from multiple-attribute regression analysis of RT, DT, GR, and DEN logs. Representative P-and S-wave velocities and Poisson＇s ratio are statistically computed for oil and water bearing reservoir rock, shale, and calcareous shale in each well. The averaged values are used for AVO forward modeling. Comparing the modeling results with actual seismic data limit the possible AVO interpretations. Well and seismic data are used to calibrate inverted P-wave, S-wave, Poisson＇s ratio, and AVO gradient attribute data sets. AVO gradient data is used for lithofacies interpretation, P-wave data is used for acoustic impedance inversion, S-wave data is used for elastic impedance, and Poisson＇s ratio data is used for detecting oil and gas. The reservoir and hydrocarbon detections are carried out sequentially. We demonstrate that the AVO attributes method can efficiently predict reservoir and hydrocarbon potential.展开更多
We applied the reflectivity method and the constrained sparse spike inverse modeling(CSSI) method to the interpretation of coal field lithologic seismic data.After introducing the principles of these two methods we di...We applied the reflectivity method and the constrained sparse spike inverse modeling(CSSI) method to the interpretation of coal field lithologic seismic data.After introducing the principles of these two methods we discuss some parameters of a geological model involving possible gas enriched areas or intruded igneous rock.The geological model was constructed and a 60 Hz seismic response profile was obtained looking for igneous rock intrusion and coked areas of the coal seam using the reflectivity method.Starting from synthesized logging data from two wells and a synthesized seismic wavelet we calibrated the model to show accurate strata.Finally,we predicted the lithology within a 10 m igneous rock area,a 3 m coal seam area,and a coked area using the CSSI technique.The results show that the CSSI technique can identify hard to recognize lithologic features that normal profil-ing methods might miss.It can quantitatively analyze and evaluate the intrusive area,the coked area,and the gas-enriched area.展开更多
文摘In the Hongze Area, the reservoirs vary rapidly laterally and are controlled by many factors, such as structure, lithology, oil source, and so on. S-wave well log curves are calculated from an equation derived from multiple-attribute regression analysis of RT, DT, GR, and DEN logs. Representative P-and S-wave velocities and Poisson＇s ratio are statistically computed for oil and water bearing reservoir rock, shale, and calcareous shale in each well. The averaged values are used for AVO forward modeling. Comparing the modeling results with actual seismic data limit the possible AVO interpretations. Well and seismic data are used to calibrate inverted P-wave, S-wave, Poisson＇s ratio, and AVO gradient attribute data sets. AVO gradient data is used for lithofacies interpretation, P-wave data is used for acoustic impedance inversion, S-wave data is used for elastic impedance, and Poisson＇s ratio data is used for detecting oil and gas. The reservoir and hydrocarbon detections are carried out sequentially. We demonstrate that the AVO attributes method can efficiently predict reservoir and hydrocarbon potential.
基金Projects 40874054 and 40804026 supported by the National Natural Science Foundation of Chinathe National Basic Research Program of China (2007CB209400 and 2009CB219603)the National Key Scientific and Technological Project (2008ZX05035)
文摘We applied the reflectivity method and the constrained sparse spike inverse modeling(CSSI) method to the interpretation of coal field lithologic seismic data.After introducing the principles of these two methods we discuss some parameters of a geological model involving possible gas enriched areas or intruded igneous rock.The geological model was constructed and a 60 Hz seismic response profile was obtained looking for igneous rock intrusion and coked areas of the coal seam using the reflectivity method.Starting from synthesized logging data from two wells and a synthesized seismic wavelet we calibrated the model to show accurate strata.Finally,we predicted the lithology within a 10 m igneous rock area,a 3 m coal seam area,and a coked area using the CSSI technique.The results show that the CSSI technique can identify hard to recognize lithologic features that normal profil-ing methods might miss.It can quantitatively analyze and evaluate the intrusive area,the coked area,and the gas-enriched area.
